sejal

writing, so i don't forget. i'll forget anyway tho.
growth @

[sejal @sejaljam]

Omg I am obsessed with @figma make

[Aaron Levie @levie]

The past couple months we may be witnessing what the Applied AI layer will look like at scale. Despite some of the initial critique that this would just be a thin layer on the LLM, it’s turning out that actually driving agentic workflows in an enterprise is far more complex. And anywhere there’s complexity you generally gain a moat and value over time.

Here are a few of the components that appear to make up the playbook based on the examples we’re collectively seeing in coding, legal, healthcare, customer support, financial services and other fields:

* Build the features that bridge the gap between the intelligence and the workflow. Some workflows can be automated by simply going to a general purpose interface, but others need tuned interfaces and features tied to the work they’re augmenting or automating. They need features that are specific to capturing the kind of data that’s needed as context for the agent. And they need a variety of bespoke tools for the agent to use, and unique interfaces for the human-in-the-loop UX. Going far deeper than just presenting the output tokens is clearly critical, and the more depth there is here definitionally the more sustaining value.

* Act as the model router balancing frontier intelligence with cheaper models. A natural advantage that any model neutral platform has is that it can naturally (in a business model-aligned way) leverage whatever level of intelligence is necessary for the workflows they’re automating to get done. There are plenty of scenarios where you need GPT-5.5 or Fable level capability, and also lots of workloads where a more efficient closed or open weights do the trick. Only the companies that have deep evals on specific tasks across all models, and the ability business model wise to leverage them, are in a great position.

* Drive the actual implementation and change management via FDE or equivalent. A big reason the applied layer works at scale is that most enterprises need some degree of help and support with change management in implementing agents for their workflows. Data has to be cleaned up and moved to modern systems, processes have to be re-engineered and documented, workflows have to be evaled, SLAs have to get achieved, and so on. All of this is going to be unique for every type of process that gets implemented, which means the companies that have expertise in a given domain and come with all the relevant best practices will be in a strong position.

* Implement domain specific GTM that creates expertise in that field. Beyond FDEs the companies that can build sales and GTM motions aligned to their domains also have a natural advantage. Most IT and line of business leaders have too many things to do in any given day; so if you’re not on their agenda, likely someone else is. Depending on the industry, there are entirely different sets of language you use, ways of working through security and compliance, regulatory controls you have to support, industry events that companies convene at, different system integrator and consulting partners you need to work with, and so on. The more generalized this gets the less you can speak the customers language, which is where the applied layer has a leg up.

A final note. There remains a view that a lot of this is all mitigated by model intelligence alone, and the bitter lesson solves all of this in the limit. That’s possibly true, but enterprises need help changing *today*. And many aspects of how to bring intelligence to real world work don’t only depend on the axis of the pure capability of the model, so most of what you’re doing now to win ends up being important no matter how good the models get.

[Hiten Shah @hnshah]

Satya’s post is worth reading closely because it gets at the real AI question for companies.

Who captures the learning?

His argument is that companies are becoming a new kind of learning system.

People bring judgment, taste, relationships, context and ambition. AI brings scale, memory, reasoning and execution. The value comes from building a loop where the company gets smarter every time work happens.

The important asset is the learning system around the model.

That system is built from the record of how work actually gets done. Workflow traces show the path people take. Corrections reveal judgment. Accepted outputs show what good looks like. Rejected approaches sharpen the standard.

Private evaluations, domain-specific context and institutional memory give that learning structure.

Over time, the company starts to retain more of what used to disappear inside meetings, edits, comments, decisions and individual experience.

That is the learning loop Satya is pointing at.

The judgment that once lived in a few people’s heads can become part of how the company operates.

[Lyn🦋 @_ayandamay]

I overheard a girl saying yesterday ‘worrying is such a terrible use of your imagination’ … and I audibly gasped.

[sejal @sejaljam]

We don't need to think.

We just need to speak and write.

[sejal @sejaljam]

I don't think women are inherently more 'emotional' than men. It's just a learned societal trait.

Biologically, women can have babies and men are slightly, physically stronger. But that's about it.

Not enough of a difference to warrant such huge imbalances in content and social/ cultural expectations expectations.

[sejal @sejaljam]

Automation is not new - we've been tactically improving, outsourcing and automating deterministic workflows for decades.

The shift in recent years is now LLMs can process vasts amounts of unstructured data, reason and produce indeterministic outputs, often autonomously (if we allow it).

We can now change the degree to which humans are in the loop for these workflows - and that's the biggest shift in how we work. We are orchestrators of agentic workflows - not just AI tools.

It's not 'set and forget'. It's 'set, monitor, improve'.

[sejal @sejaljam]

Business transformation is radically different today - we are re-inventing organisations with agentic architectures as the foundation. The pipeline is fundamentally different. So is the capability model.

[sejal @sejaljam]

real laziness is making things overly complex for yourself and everyone just so you can appear intelligent. what a waste of gobbly time, and actual dumb

[sejal @sejaljam]

The real shift from 'AI' is architectural via agentic systems, not incremental improvements via 'AI tooling'

[sejal @sejaljam]

Automation is not 'new'. The real break-through with this 'LLM' era is that we now we have access to shared context.

The knowledge always existed. The difference now is that we can capitalise on this vastness of human knowledge via access to models trained on vast amounts of data.

We can access it through natural language, voice - cheaply and abundantly.

Unlimited access has unlocked our ability to create more in a far more democratised manner.

That's the shift in work. Abundance is the new norm.

Abundant knowledge.

The task for human capital is to now compound on our tacit knowledge using LLMs as a lever for growth.

[sejal @sejaljam]

laughed out life. hope its meeee

[Libriscent @libriscent]

You guys ever think about how there's random people out there who have a story about the weirdest person they've ever encountered and it's you

[sejal @sejaljam]

bruh

[du @thedulab]

High pressure situations are fun. You can learn to love them. Whenever I find myself in one, I always entertain the thought of some random person being in a similar position and how they might react. Imagining them making a fool of themselves, even if this is purely hypothetical

Then I'm just like "I could crash out and get all flustered too but how utterly embarrassing would that be" and immediately get this burst of energy. Forces you to showcase some arrogance but unlike fake comparison games involving status and what not, this is one that actually replenishes instead of drains your life force

Trains your mind to embrace these free opportunities to say "I'm a winner" where your confidence is now attached to how you respond to adversity which you have full control over. Keep responding with poise and eventually it becomes your default. Smile and laugh just because you can while others need external permission. Unstoppable

[Jack Kuveke @jackkuveke]

AI just took my fucking job

[sejal @sejaljam]

ok this is damn funny

[Spencer Shulem @Spshulem]

Me and Fable 5 for the 3 days I had her

[sejal @sejaljam]

i would post this on instagram if i still had instagram

[Path of Men @PathOfMen_]

You're supposed to use every unfair advantage you have. Looks, genetics, connections, dad's money, whatever.

There's nothing noble about choosing the hardest path just to feel like an underdog.

[Zoey @Zoey168102]

Normalize being very direct, very straight to the point and very assertive. A surprising amount of tension in adult life exist because people avoid saying what they actually mean.

[Satya Nadella @satyanadella]

https://t.co/vLmiBKTtX3

[sejal @sejaljam]

Trust gut.

Work to gut.

Hold high conviction to gut.

Fail to gut.